CNN-based Prediction of Network Robustness With Missing Edges

Connectivity and controllability of a complex network are two important issues that guarantee a networked system to function. Robustness of connectivity and controllability guarantees the system to function properly and stably under various malicious attacks. Evaluating network robustness using attack simulations is time consuming, while the convolutional neural network (CNN)-based prediction approach provides a cost-efficient method to approximate the network robustness. In this paper, we investigate the performance of CNN-based approaches for connectivity and controllability robustness prediction, when partial network information is missing, namely the adjacency matrix is incomplete. Extensive experimental studies are carried out. A threshold is explored that if a total amount of more than 7.29\% information is lost, the performance of CNN-based prediction will be significantly degenerated for all cases in the experiments. Two scenarios of missing edge representations are compared, 1) a missing edge is marked `no edge' in the input for prediction, and 2) a missing edge is denoted using a special marker of `unknown'. Experimental results reveal that the first representation is misleading to the CNN-based predictors.Comment: In Proceedings of the IEEE 2022 International Joint Conference on Neural Networks (IJCNN

Proton Isovector Helicity Distribution on the Lattice at Physical Pion Mass

We present a state-of-the-art calculation of the isovector quark helicity Bjorken-$x$ distribution in the proton using lattice-QCD ensembles at the physical pion mass. We compute quasi-distributions at proton momenta $P_z \in \{2.2, 2.6, 3.0\}$~GeV on the lattice, and match them systematically to the physical parton distribution using large-momentum effective theory (LaMET). We reach an unprecedented precision through high statistics in simulations, large-momentum proton matrix elements, and control of excited-state contamination. The resulting distribution with combined statistical and systematic errors is in agreement with the latest phenomenological analysis of the spin-dependent experimental data; in particular, $\Delta \bar{u}(x)>\Delta \bar{d}(x)$.Comment: 6 pages, 4 figure

Strong magnon-magnon coupling in an ultralow damping all-magnetic-insulator heterostructure

Magnetic insulators such as yttrium iron garnets (YIGs) are of paramount importance for spin-wave or magnonic devices as their ultralow damping enables ultralow power dissipation that is free of Joule heating, exotic magnon quantum state, and coherent coupling to other wave excitations. Magnetic insulator heterostructures bestow superior structural and magnetic properties and house immense design space thanks to the strong and engineerable exchange interaction between individual layers. To fully unleash their potential, realizing low damping and strong exchange coupling simultaneously is critical, which often requires high quality interface. Here, we show that such a demand is realized in an all-insulator thulium iron garnet (TmIG)/YIG bilayer system. The ultralow dissipation rates in both YIG and TmIG, along with their significant spin-spin interaction at the interface, enable strong and coherent magnon-magnon coupling with a benchmarking cooperativity value larger than the conventional ferromagnetic metal-based heterostructures. The coupling strength can be tuned by varying the magnetic insulator layer thickness and magnon modes, which is consistent with analytical calculations and micromagnetic simulations. Our results demonstrate TmIG/YIG as a novel platform for investigating hybrid magnonic phenomena and open opportunities in magnon devices comprising all-insulator heterostructures.Comment: 45 pages, 18 figures, and 2 table

Experimental evidence for Berry curvature multipoles in antiferromagnets

Berry curvature multipoles appearing in topological quantum materials have recently attracted much attention. Their presence can manifest in novel phenomena, such as nonlinear anomalous Hall effects (NLAHE). The notion of Berry curvature multipoles extends our understanding of Berry curvature effects on the material properties. Hence, research on this subject is of fundamental importance and may also enable future applications in energy harvesting and high-frequency technology. It was shown that a Berry curvature dipole can give rise to a 2nd order NLAHE in materials of low crystalline symmetry. Here, we demonstrate a fundamentally new mechanism for Berry curvature multipoles in antiferromagnets that are supported by the underlying magnetic symmetries. Carrying out electric transport measurements on the kagome antiferromagnet FeSn, we observe a 3rd order NLAHE, which appears as a transverse voltage response at the 3rd harmonic frequency when a longitudinal a.c. current drive is applied. Interestingly, this NLAHE is strongest at and above room temperature. We combine these measurements with a scaling law analysis, a symmetry analysis, model calculations, first-principle calculations, and magnetic Monte-Carlo simulations to show that the observed NLAHE is induced by a Berry curvature quadrupole appearing in the spin-canted state of FeSn. At a practical level, our study establishes NLAHE as a sensitive probe of antiferromagnetic phase transitions in other materials, such as moir\'e superlattices, two-dimensional van der Waal magnets, and quantum spin liquid candidates, that remain poorly understood to date. More broadly, Berry curvature multipole effects are predicted to exist for 90 magnetic point groups. Hence, our work opens a new research area to study a variety of topological magnetic materials through nonlinear measurement protocols

Field Emission of Multi-Walled Carbon Nanotubes from Pt-Assisted Chemical Vapor Deposition

Multi-walled carbon nanotubes (MWNTs) were grown directly on a metal substrate with the assistance of Pt using a chemical vapor deposition method. In addition, the growth mechanism of Pt-assisted catalytic CNT was discussed. MWNTs were characterized by SEM, TEM, AFM, Raman, and EDS, and the field emission (FE) properties were investigated, comparing with the direct grown MWNTs. The results showed that CNTs could not been synthesized by Pt particles alone under the experimental condition, but Pt may accelerate the decomposition of the carbon source gas, i.e., assisting MWNT growth with other catalysts. The Pt-assisted MWNTs were longer with larger diameters of around 80 nm and possessed better structural qualities with very few catalyst particles inside. Improved field emission properties were demonstrated for the Pt-assisted MWNTs with lower turn-on fields (for 0.01 mA·cm−2 current density) of 2.0 V·μm−1 and threshold field (for 10 mA·cm−2 current density) of 3.5 V·μm−1, as well as better stability under a long-term test of 80 h (started at 3.0 mA for the Pt-assisted emitter and 3.25 mA for the direct grown emitter). This work demonstrated a promising approach to develop high performance CNT field emitters for device applications

Generating Giant Membrane Vesicles from Live Cells with Preserved Cellular Properties

Biomimetic giant membrane vesicles, with size and lipid compositions comparable to cells, have been recognized as an attractive experimental alternative to living systems. Due to the similarity of their membrane structure to that of body cells, cell-derived giant plasma membrane vesicles have been used as a membrane model for studying lipid/protein behavior of plasma membranes. However, further application of biomimetic giant membrane vesicles has been hampered by the side-effects of chemical vesiculants and the utilization of osmotic buffer. We herein develop a facile strategy to derive giant membrane vesicles (GMVs) from mammalian cells in biofriendly medium with high yields. These GMVs preserve membrane properties and adaptability for surface modification and encapsulation of exogenous molecules, which would facilitate their potential biological applications. Moreover, by loading GMVs with therapeutic drugs, GMVs could be employed for drug transport to tumor cells, which represents another step forward in the biomedical application of giant membrane vesicles. This study highlights biocompatible GMVs with biomimicking membrane surface properties and adaptability as an ideal platform for drug delivery strategies with potential clinical applications